System and method for patterned artifact removal for bitonal images

ABSTRACT

Images in bitonal formats often include watermarks, stamps, or other patterns and artifacts. These patterned artifacts may be represented as a series of geometric points, dots, and/or dashes in the general shape of the original pattern. These patterned artifacts make other processes such as optical character recognition (OCR) difficult or impossible when items or pixels of interest are also found within the pattern of such artifact(s). Current patterned artifact removal solutions use methods of erosion to minimize the unwanted patterned artifact. However, such methods also erode the pixels/items of interest which, in turn, cause failures in other processes, such as OCR, that are desired to be carried out on or with the image.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority from U.S. patent application Ser. No.15/839,133 for SYSTEM AND METHOD FOR PATTERNED ARTIFACT REMOVAL FORBITONAL IMAGES filed Dec. 12, 2017 and Provisional Patent ApplicationSer. No. 62/434,208, entitled PATTERNED ARTIFACT REMOVAL FOR BITONALIMAGES, filed Dec. 14, 2016, the entire contents of which areincorporated herein by reference.

BACKGROUND

Images in bitonal formats often include watermarks, stamps, or otherpatterns and artifacts. These patterned artifacts may be represented asa series of geometric points, dots, and/or dashes in the general shapeof the original pattern. These patterned artifacts make other processessuch as optical character recognition (OCR) difficult or impossible whenitems or pixels of interest are also found within the pattern. Currentpatterned artifact removal solutions use methods of erosion to minimizethe unwanted patterned artifact. However, such methods also erode thepixels/items of interest which, in turn, cause failures in otherprocesses, such as OCR, that are desired to be carried out on or withthe image.

SUMMARY

The present disclosure relates to a computer-implemented system andmethod for the removal of unwanted patterned artifacts that may overlapdesired information or pixels/items of interest on a bitonal image andmaintaining the integrity of the desired information or pixels/items ofinterest. Unwanted patterned artifacts might be added to a documentprior to scanning, or are created when a document is scanned, or areotherwise present at the time the document is scanned.

A method for removing a patterned artifact from an initial bitonalimage, the method being performed by one or more processors andcomprising identifying the patterned artifact in the initial bitonalimage, removing the patterned artifact to create a new bitonal imagewith the patterned artifact substantially removed; identifying text inthe new bitonal image; and cleaning the new bitonal image to remove oneor more remaining portions of the patterned artifact and thereby createa second new bitonal image.

A method for removing a patterned artifact from an initial bitonalimage, the method being performed by one or more processors andcomprising the steps of: (a) identifying the patterned artifact in theinitial bitonal image. Wherein the identifying the patterned artifactstep includes generating a modified image by applying an erosionalgorithm based on stroke width of the initial image, and defining, inthe modified image, an artifact boundary and thereby identify thepatterned artifact. The method also includes step (b), removing thepatterned artifact to create a new bitonal image with the patternedartifact substantially removed.

A method for removing a patterned artifact from an initial bitonalimage, the method being performed by one or more processors andcomprising: (a) identifying the patterned artifact in the initialbitonal image; (b) removing the patterned artifact to create a newbitonal image with the patterned artifact substantially removed, (c)identifying text in the new bitonal image, and (d) cleaning the newbitonal image to remove one or more remaining portions of the patternedartifact and thereby create a second new bitonal image. Wherein theidentifying the patterned artifact step includes: (i) generating amodified image by applying an erosion algorithm based on stroke width ofthe initial image; (ii) marking noise locations of the modified image;and (iii) defining, in the modified image, an artifact boundary andthereby identify the patterned artifact. Wherein the removing thepatterned artifact step includes: (i) applying one or more filters inthe artifact boundary defined from the identifying the patternedartifact step; (ii) dilating the identified patterned artifact; and(iii) removing areas having a size larger than areas marked as noisefrom the marking step of the identifying the patterned artifact step andthereby creating the new bitonal image with the patterned artifactsubstantially removed. Wherein the step of identifying text in the newbitonal image includes: (i) identifying text in the new bitonal image;(ii) rank reducing the identified text to create one or more potentialblocks of text; (iii) a first removing of one or more remaining portionsof the patterned artifact through applying a binary AND operation on theidentified text from the identifying text in the new bitonal image stepwith the one or more potential blocks of text from the rank reducingstep to create a first intermediate bitonal image of the new bitonalimage; (iv) dilating the first intermediate bitonal image; and (v)comparing the dilated first intermediate bitonal image with the initialbitonal image within the artifact boundary defined from the identifyingthe patterned artifact step thereby further removing the one or moreremaining portion of the patterned artifact and creating a secondintermediate bitonal image of the new bitonal image. Wherein thecleaning the new bitonal image step includes: cleaning the secondintermediate bitonal image by applying a binary AND operation on thesecond intermediate bitonal image with the initial bitonal image withinthe artifact boundary defined from the identifying the patternedartifact step and thereby create the second new bitonal image.

A non-transitory computer-readable storage media having stored thereon aplurality of computer-executable instructions for removing a patternedartifact from an initial bitonal image which, when executed by aprocessor, cause the processor to: identify the patterned artifact inthe initial bitonal image, wherein the identification of the patternedartifact in the bitonal image includes generating a modified image byapplying an erosion algorithm based on stroke width of the initialimage; and defining, in the modified image, an artifact boundary andthereby identify the patterned artifact, remove the patterned artifactto create a new bitonal image with the patterned artifact substantiallyremoved, and clean the new bitonal image to remove one or more remainingportions of the patterned artifact and thereby create a second newbitonal image.

A system comprising: a processor; and a computer-readable storage mediaoperably connected to said processor. The computer-readable storagemedia includes instructions that when executed by the processor, causeperformance of the processor to remove a patterned artifact from aninitial bitonal image by performing operations including: identify thepatterned artifact in said initial bitonal image; remove the patternedartifact to create a new bitonal image with the patterned artifactsubstantially removed; identify text in the new bitonal image; and cleanthe new bitonal image to remove one or more remaining portion of thepatterned artifact and thereby create a second new bitonal image.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A illustrates a portion of a bitonal image containing an unwantedpatterned artifact in the form of a watermark text reading“Non-negotiable” overlapping certain items of interest.

FIG. 1B is an enlargement of a portion of FIG. 1 a.

FIG. 2 is a simplified flowchart of a method for removing a patternedartifact from a bitonal image.

FIGS. 3A-3P show a simplified visual depiction of a method for removinga patterned artifact from a bitonal image.

FIG. 4A is a reproduced image of the initial image depicted in FIG. 3A.

FIG. 4B is a reproduced image of the modified image of FIG. 3J with theartifact(s) removed.

FIG. 4C is a reproduced image of the modified image of FIG. 3P after theoptional clean up steps have occurred.

FIG. 5 is a simplified block diagram that shows an example of acomputing system for removing unwanted patterned artifacts on a bitonalimage.

DETAILED DESCRIPTION

The system and method described herein focus on removing unwantedpatterned artifacts 102 found on bitonal images 100. The unwantedpatterned artifacts 102 may have been added to a document post-print andprior to scanning, or may have been created when a document is scanned,or are otherwise present at the time the document is scanned. Theunwanted patterned artifacts 102 may generally be present in a bitonalimage 100 as a plurality of unconnected dots or dashes. For example, thetext “NON-NEGOTIABLE” depicted in FIG. 1A, FIG. 11 (a portion thereof),and FIG. 3A is an example of a patterned artifact 102 overlapping otheritems, e.g. items of interest or desired information 103, on the bitonalimage 100.

A simplified block diagram of a computer-implemented method for removinga patterned artifact from a bitonal image is depicted in FIG. 2. Thedescribed method and techniques can be performed using one or morecomputing systems 500 as will be described further. In FIG. 2 an initialor original image 100 in bitonal format is provided, e.g. scanned intoor otherwise provided to a computing device 502 in a computing system500. An example initial image 100 in bitonal format having one or morepatterned artifacts 102 is depicted in FIGS. 3A and 4A.

Referring to FIG. 2, a computer-implemented method includes step 202 ofidentifying a patterned artifact 102 in an initial bitonal image 100.The identifying step 202 includes using noise and dot detectionprocesses. Connected component analysis is conducted followed byapplying one or more different filters. For example, the one or moredifferent filters include a dot filter, a general noise filter, and adash filter. For example, NISTIR 5843, Component-Based HandprintSegmentation Using Adaptive Writing Style Model, Michael D. Garris,National Institute of Standards and Technology, 1996, the entirety ofwhich is incorporated by reference, describes different filters. Forexample, the noise, dot, and dash filters of Garris include, the noisefilter at page 22, A.1; the dot filter at page 22 A.2; and the dashfilter at page 24, A.7 regarding “dash-like” component, each of whichare reproduced below in Table 1.

TABLE 1 A.1 Is If (c.a < (0.5 × ssa) then Noise Noise? where structuremember (a) is the pixel area of the component (c) and ssa is the pixelarea of a standard stroke width A.2 is If (c.w < (2 × esw)) && (c.h. <(3 × esw)) then Dot Dot? where structure member (w) is the pixel widthof the component (c) and esw is the estimated stroke width. This allowsa small diagonal stroke to be considered a dot. Handprinted dots areseldom square, but they are typically a small tick-mark A.7 Is If (topis shorter && not too far right && not too far left && Top of not toofar down && dash-like) then Top of 5 5? where the tests for topcomponent candidate (t) with left neighbor component (n) are shorter:(t.h < n.h) too far right: ((t.x1 − t,x2) < min((t.w × 0.5), (n.w ×0.5))) too far left: ((n.x1 − t.x1) < min((t.w × 0.5), (n.w × 0.5))) toofar down: ((t. y2 − n.y1) < (n.w × 0.5)) dash-like: ((t.p/esw) < (t.1 +esw)) and the structure member (p) is the black pixel count of thecomponent and (1) is the diagonal length of the component. The tophorizontal stroke of a 5 is frequently written so that it is detachedfrom its body. This stroke is dash-like, meaning the component iscomprised of a single horizontal stroke that spans the entire width ofthe image. The height of the stroke should be uniformly close to theestimated stroke width, so dividing the black pixel count in thecomponent by the estimate stroke width should be very close to thediagonal length of the component (at least within a stroke width:,

With reference to FIG. 2, the identifying step 202 includes, a step ofreducing noise 204 by applying a noise reduction filter to the initialbitonal image 100. The identifying step 202 may further include at step206, applying an erosion algorithm based on stroke width of the image tocreate a series of isolated dots to aid in identifying noise locations.For example, a binary morphology erosion algorithm may be used. Theresultant visual image from applying the erosion algorithm in step 206is illustrated in FIG. 3B. The resulting image depicted in FIG. 3B is arectangle structure element with dimensions of half estimated strokewidth for horizontal and three-quarters estimated stroke width forvertical direction.

The process for determining the stroke width is explained in NISTIR5843, Component-Based Handprint Segmentation Using Adaptive WritingStyle Model, Michael D. Garris, National Institute of Standards andTechnology, 1996, the entirety of which is incorporated by reference.The formulation of the stroke width is found on page 5 in the firstparagraph of section three of Garris. It is defined as “the medianhorizontal run length in the image.”

The method proceeds to step 208 to mark the noise locations within thestructuring element found from step 206. The marked noise locations ofstep 208 are illustrated in FIG. 3C using the noise filter describedabove; however, any other noise detection algorithms known in the artthat provide for similar results described in the present disclosure arealso suitable. The identifying step 202 further includes step 210 ofdetecting the boundary of the patterned artifact 102 or cluster via awindowed search. FIGS. 3D-3F depict a visual representation of step 210.An initial forward pass for boundary detection occurs. For ease ofreference and for exemplary purposes only, the measurements providedthroughout this disclosure assume a resolution of 300 dpi (dots perinch) both in the x- and y-directions. Other resolutions andmeasurements can be used for various resolutions. For example, theforward pass may include a windowed detection from top to bottom, leftto right with a size of twenty-nine (29) pixels wide and tall. By way ofexample, each window location may be defined to must have a minimum offive (5) “noise” connected components contained within the window. Forexample, upon detection, a black square with dimensions of sixty-eight(68) pixels wide and tall centered on the found point is output. FIG. 3Dis the visual representation of the result of the forward pass boundarydetection in connection with the herein described example resolution andnumerical values. Step 210 of detecting the boundary of patternedartifact 102 of the identifying step 202 further includes a reverse passfor boundary detection, the resulting visual output is depicted in FIG.3E. The reverse pass is the same as the forward pass described hereinexcept that the windowed operation proceeds from bottom to top, right toleft. FIG. 3F is representative of the result of a binary “AND”operation on the output of the forward pass boundary detection of FIG.3D with the reverse pass boundary detection of FIG. 3E, thereby definingthe boundary of artifact 102. The dimensions of the windowed search andnumerical value of the noise count of the “noise connected components”of the present disclosure are not limited to the numerical valuesdisclosed but are provided for representative purposes only, otherdimensions and numeral values may be used.

Once artifact area boundary is identified the system and method proceedto step 212 of removing the identified patterned artifact 102.

With reference to visual representation depicted in FIG. 3G, anintersection of all eroded information and the artifact area isidentified for further processing. As shown in FIG. 3G, noise isfiltered in step 214 through application of a noise filter. The noiseidentified in step 208 and visually depicted in FIG. 3C undergoes abinary “AND” operation to thereby limit the subsequent method steps tothe area defined within the boundary obtained in step 210 (the boundarybeing visually depicted in FIG. 3F). The removal step 212 includes adilating step 216, for example, binary morphology dilation may be used.FIG. 3H provides a visual example of the resultant patterned artifact102 after undergoing the binary morphology dilation processing step of216.

The removal step 212 further includes step 218 of applying noise filtersto remove the patterned artifact 102 while leaving the desiredinformation or items of interest 103, such as lines and characterfields. For example, with reference to FIG. 3I, the removal step 212proceeds to step 218 to remove the areas defined as noise from step 208from the initial image 100 depicted in FIG. 3A. The areas defined asnoise are removed using an area size of a few pixels larger than thesize of the noise, e.g. two (2) pixels or any other suitable value thatdoes not cause a significant loss of to the desired information 103.

The removal step 212 further includes step 220 of re-evaluating thenoise. With reference to the visual depiction shown in FIG. 3J, noisewith the characteristics of dot width of eight (8), dot height of twelve(12), and a noise threshold of eight (8) with a four-pixel boundaryusing a binary “AND” operation on the results of the previous operation,e.g. step 218 visually depicted in FIG. 3I with that of the originalimage 100 visually depicted in FIG. 3A. FIGS. 3J and 4B depict theresulting new bitonal image 104 with most or a substantial portion ofthe patterned artifact 102 removed.

With reference to FIG. 2, the system and method may optionally furtherinclude additional processing on the new bitonal image 104. For example,additional processing may include step 222 of text identification andclean-up of the image 104 to remove “hair” or “tails” or line trails 105remaining within the defined boundary found earlier. An example of theremaining unwanted patterned artifact in the form of “hair” or “tails”105 is shown in FIG. 3J in the word “charge”.

To remove the remaining unwanted patterned artifacts 105, the image 104of FIG. 3J may then be dilated slightly higher than what was previouslydone with reference to step 206, visually depicted as FIG. 3B. Thedilated image may then be compared with the original bitonal image 100depicted in FIG. 3A but only within the defined area or boundary thatwas found earlier.

For example, with reference to the visual depiction at FIG. 3K, at step224 the system and method proceeds to identify potential blocks of text,in this case the text of desired information or items of interest 103.Potential blocks are identified by any text segmentation algorithm,including a “smearing” methodology as described in Wong K., R. Casey, F.Wahl (1982), Document analysis systems, IBM Journal of research anddevelopment, Vol 26, no 6, the entirety of which is incorporated byreference. FIG. 3K illustrates the result of identifying potentialblocks of text of the image of FIG. 3J.

Step 222 may further include step 226, rank reducing the text asvisually depicted in FIG. 3L. The text of FIG. 3J is rank reduced byfour (4) thereby causing the text to become blocked which helps aid inremoval of the one or more remaining portions 105 of the patternedartifact 102.

Step 228 of removing the one or more remaining portions 105 of artifact102 of the text identification and clean up step 222 is visuallydepicted in FIG. 3M. FIG. 3M depicts the result of a binary “AND”operation of the text block of identified at step 224 of FIG. 3K withthe rank reduced text of step 226 depicted in FIG. 3L, thereby removingone or more remaining portions 105 of artifact 102.

The text identification and clean up step 222 further includes adilating step 230 by dilating the image depicted in FIG. 3M. Forexample, the image of FIG. 3M is dilated where the structuring elementis a rectangle with dimensions of two pixels in both the horizontal andvertical directions. FIG. 3N is the resultant image of the dilating step230 via binary morphology dilation.

The text identification and clean up step 222 further includes removingthe one or more remaining portions 105 of the patterned artifact 102 byutilizing a comparison step 232 by applying a binary “AND” operation ofthe dilated image depicted in FIG. 3N with the original image 100depicted in FIG. 3A within the artifact boundary defined by the priorsteps discussed above to produce the resultant image 106 shown in FIG.3O.

The text identification and clean up step 222 further includes step 234of cleaning up image 106 to achieve a second new or second modifiedbitonal image 108 depicted in FIG. 3P and FIG. 4C. FIG. 3P is the resultof performing a binary “AND” operation on image 106 depicted in FIG. 3Owith the original image 100 depicted in FIG. 3A and only within thedefined boundary which was previously found as described above withreference to FIG. 3F.

Table 2 shows an example of a sample of how the disclosedcomputer-implemented methods, systems, and techniques described hereinincreases accuracy of identifying patterned artifacts 102, removing theartifact 102, and maintaining the integrity of the items of interest 103of a given bitonal image.

TABLE 2 Total Characters 6,304 Total Original Misreads 5,085 80.7% TotalMisreads AFTER Removal 1,191 18.9% Improvement 3,894 61.8%

As shown in Table 2, in the sample, 6,304 characters were reviewed.Approximately 80.7%, i.e. 5,085 characters, were misread when thecomputing systems and described methods and techniques for patternedartifact removal was not applied. When the described patterned artifactremoval systems, techniques, and methodology was implemented on the sameset of characters, only 1,191 characters or 18.9% resulted in a misread,thereby showing that the presently described systems, techniques, andmethods result in an improvement for recognizing patterned artifact(s),removing the artifact(s), and maintaining the integrity of the items ofinterest of 61.8% or 3,894 characters of the given data set.

FIG. 5 is a simplified block diagram for a computing system 500 suitablefor implementing and performing the methods and techniques describedherein. Computing system 500 includes a computing device 502 operablyconnected to one or more input/output (I/O) devices 508. Computingdevice 502 is representative of various forms of computing devices,including desktops, laptops, workstations, servers, mobile devices, suchas personal digital assistants, tablets, smart-phones, cellulartelephones, and other similar computing devices.

Computing device 502 includes a central processing unit (CPU) 504. CPU504 includes one or more processors reading and/or executinginstructions, programs, and applications stored in memory 506 and/orcomputer readable storage media of I/O devices 508, and accessing and/orstoring data in memory 506 and/or computer readable storage media of I/Odevices 508. CPU is operably connected with memory 506. CPU 504 is alsooperably connected with I/O devices 508 through an applicable interfacecomponent for the corresponding I/O device 508, e.g. port (serial,parallel USB), wire, card (sound, video, network), and the like.Exemplary types of CPU 504 may include general purpose processors,digital programmable devices, microcontrollers, digital signalprocessors (DSPs), application specific integrated circuit (ASIC), andfield programmable gate array (FPGA), or other components andcombinations thereof designed to perform the functions described herein.

Memory 506 includes data storage, volatile memory, e.g. random accessmemory (RAM), and non-volatile memory, e.g. read only memory (ROM).

I/O devices 508 include various devices that a user may use to interactwith the computing device 502. Representative I/O devices 508 includekeyboards, touchscreens, mouse and other pointing devices; a visualdisplay device, such as a cathode ray tube, liquid crystal display,screens, and other suitable display devices for visually communicatingand interacting with the user; audio devices, such as a microphone,headphones, speakers; and print devices for printing, scanning, faxing,and/or receiving and/or transmitting data and images. I/O devices 508may also include computer readable storage media, e.g. mass storagedevices, disks, magnetic disks, optical disks, magnetic tape, flashmemory, RAM, ROM, EEPROM, or any other media that can be used to carryor store computer-readable information. I/O devices 508 may also includea communication device for connecting computing system 500 with one ormore other computing systems over a network, e.g. wired and/orwirelessly, utilizing one or more communications protocols, e.g. IEEE802.11, IEEE 802.3, TCP/IP, cellular protocols, any other communicationsprotocols, and combinations thereof.

System 500 may include one or more I/O devices 508 of the same type orof different types and combinations thereof and one or more computingdevices 502 of the same type or of different types and combinationsthereof may be operably connected to each other and cooperating togetherto carry out the methods, functions, and techniques described herein.

The functions, methods, or algorithms described herein may beimplemented in hardware, software, firmware, or any combinationsthereof. When implemented in software, the described methods, functions,and techniques may be stored in memory, computer-readable storage media,and/or combinations thereof and transmitted as one or more instructionsor code to cause CPU 504 to operate in accordance with the methods,functions, techniques, and teachings of the present disclosure. Theoperable connection of the various components of computing system 500described in reference to FIG. 5 may include buses, circuitry, wires,wireless, or other similar connections. The functions, methods, andtechniques described herein may be implemented by one or more computingsystem 500 in cooperation with each other. The components of system 500shown and described, including their relationships and functions, areexemplary and are not to limit the implementation of the systems,methods, and techniques described herein.

As previously discussed above, the inclusion of certain numerical valuesfor defining areas, dilation, rank reducing, etc. are for exemplarypurposes only and the system, method, functions, and techniquesdescribed herein are not intended to be limited to those values.Adjustment of the numerical values are within the skills and knowledgeof a person skilled in the art and the numerical values used may differper application and use of the presently described system, method,functions, and techniques.

Although certain steps are described herein and illustrated in thefigures as occurring sequentially, some steps may occur simultaneouslywith each other or in an order that is not depicted. The presentdisclosure of the disclosed system, methods, techniques, and functionsare not to be limited to the precise descriptions and illustrations.Other embodiments will be apparent to one skilled in the art. As such,the foregoing description merely enables and describes the general usesof the described systems, methods, and techniques. While certainembodiments of the systems, methods, and techniques have been describedfor the purpose of this disclosure, those skilled in the art can makechanges without departing from the spirit and scope thereof. Thus, theappended claims define what is claimed.

What is claimed is:
 1. A method for removing a patterned artifact froman initial bitonal image, the method being performed by one or moreprocessors and comprising the steps of: identifying the patternedartifact in the initial bitonal image, wherein the step of identifyingthe patterned artifact in the initial bitonal image includes applying anerosion algorithm based on stroke width of the initial image to generatea modified image, marking noise locations in the modified image, andafter marking noise locations, defining an artifact boundary in themodified image, and creating a new bitonal image with the patternedartifact substantially removed, wherein the creating a new bitonal imagestep includes: applying one or more filters in the artifact boundary;dilating the identified patterned artifact; and removing areas having asize larger than areas marked as noise and thereby creating the newbitonal image with the patterned artifact substantially removed.
 2. Themethod of claim 1, further comprising the step of: cleaning the newbitonal image to remove one or more remaining portions of the patternedartifact and thereby create a second new bitonal image.
 3. The method ofclaim 1 further comprising the step of identifying text in the newbitonal image, wherein the step of identifying text in the new bitonalimage includes: rank reducing the identified text to create one or morepotential blocks of text; a first removing of one or more remainingportions of the patterned artifact through applying a binary ANDoperation on the identified text from the identifying text in the newbitonal image step with the one or more potential blocks of text fromthe rank reducing step to create a first intermediate bitonal image ofthe new bitonal image; dilating the first intermediate bitonal image;and comparing the dilated first intermediate bitonal image with theinitial bitonal image within the artifact boundary defined from theidentifying the patterned artifact step thereby further removing the oneor more remaining portions of the patterned artifact and creating asecond intermediate bitonal image of the new bitonal image.
 4. Themethod of claim 3, further comprising the step of cleaning the secondintermediate bitonal image by applying a binary AND operation on thesecond intermediate bitonal image with the initial bitonal image withinthe artifact boundary defined from the identifying the patternedartifact step and thereby create a second new bitonal image.
 5. Anon-transitory computer-readable storage media having stored thereon aplurality of computer-executable instructions for removing a patternedartifact from an initial bitonal image which, when executed by aprocessor, cause the processor to: identify the patterned artifact inthe initial bitonal image, wherein the identification of the patternedartifact in the initial bitonal image includes generation of a modifiedimage by application of an erosion algorithm based on stroke width ofthe initial image; marking of noise in the modified image, anddefinition of an artifact boundary in the modified image; create a newbitonal image with the patterned artifact substantially removed, whereinthe creation of a new bitonal image with the patterned artifactsubstantially removed includes: application of one or more filters inthe artifact boundary of the modified image, dilation of the identifiedpatterned artifact, removal of areas having a size larger than areasmarked as noise; and prior to cleaning the new bitonal image, identifytext in the new bitonal image and clean the new bitonal image to removeone or more remaining portions of the patterned artifact and therebycreate a second new bitonal image.
 6. The non-transitorycomputer-readable storage media of claim 5, wherein the identificationof text in the new bitonal image includes: rank reduction of theidentified text to create one or more potential blocks of text; a firstremoval of one or more remaining portions of the patterned artifactthrough application of a binary AND operation on the identified textfrom the identification of text in the new bitonal image with the one ormore potential blocks of text from the rank reduction of the identifiedtext to create a first intermediate bitonal image of the new bitonalimage; dilation of the first intermediate bitonal image; and comparisonof the dilated first intermediate bitonal image with the initial bitonalimage within the artifact boundary and thereby causing further removalof the one or more remaining portions of the patterned artifact andcreation of a second intermediate bitonal image of the new bitonalimage.
 7. The non-transitory computer-readable storage media of claim 5,wherein the clean the new bitonal image includes: cleaning the secondintermediate bitonal image by application of a binary AND operation onthe second intermediate bitonal image with the initial bitonal imagewithin the artifact boundary defined from the identification of thepatterned artifact and thereby results in creation of the second newbitonal image.
 8. A system comprising: a processor; and acomputer-readable storage media operably connected to said processor,said computer-readable storage media including instructions that whenexecuted by said processor, cause performance of said processor toremove a patterned artifact from an initial bitonal image by performingoperations including: identify the patterned artifact in the initialbitonal image, wherein the identification of the patterned artifact inthe initial bitonal image includes: generation of a modified image byapplication of an erosion algorithm based on stroke width of the initialimage, marking of noise in the modified image, and definition of anartifact boundary in the modified image; create a new bitonal image withthe patterned artifact substantially removed, wherein the creation of anew bitonal image with the patterned artifact substantially removedincludes: application of one or more filters in the artifact boundary ofthe modified image, dilation of the identified patterned artifact,removal of areas having a size larger than areas marked as noise; cleanthe new bitonal image to remove one or more remaining portions of thepatterned artifact and thereby create a second new bitonal image; andidentify text in the new bitonal image prior to cleaning the new bitonalimage.
 9. The system of claim 8, wherein the operation of identificationof text in the new bitonal image includes: rank reduction of theidentified text to create one or more potential blocks of text; a firstremoval of one or more remaining portions of the patterned artifactthrough application of a binary AND operation on the identified textfrom the identification of text in the new bitonal image with the one ormore potential blocks of text from the rank reduction of the identifiedtext to create a first intermediate bitonal image of the new bitonalimage; dilation of the first intermediate bitonal image; and comparisonof the dilated first intermediate bitonal image with the initial bitonalimage within the artifact boundary and thereby causing further removalof the one or more remaining portions of the patterned artifact andcreation of a second intermediate bitonal image of the new bitonalimage.
 10. The system of claim 8, wherein the operation of clean the newbitonal image includes: cleaning the second intermediate bitonal imageby application of a binary AND operation on the second intermediatebitonal image with the initial bitonal image within the artifactboundary defined from the operation of the identification of thepatterned artifact and thereby results in creation of the second newbitonal image.